Computer Vision: Face Recognition Quick Starter in Python

Preview this course

This course is designed for beginners or anyone who wants to get started with Python-based face recognition. In this course, you will learn how to perform face detection from images, face detection from real-time videos, emotion detection, age-gender prediction, face recognition from images and real-time videos, and more!

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48 on-demand videos & exercises
Level: Beginner
English
4hrs 15mins
Access on mobile, web and TV

What to know about this course

This course will help you delve into face recognition using Python without having to deal with all the complexities and mathematics associated with the deep learning process.

You will start with an introduction to face detection and face recognition technology. After this, you’ll get the system ready by installing the Anaconda package and other dependencies and libraries. You will then write Python code to detect faces from a given image and extract the faces as separate images. Next, you’ll focus on face detection by streaming a real-time video from the webcam. Customize the face detection program to blur the detected faces dynamically from the webcam video stream. You will also learn facial expression recognition and age and gender prediction using a pre-trained deep learning model. Later, you’ll progress to writing Python code for face recognition, which will help identify the faces that are already detected. Then you’ll explore the concept of face distance and tweak the face landmark points used for face detection.

By the end of this course, you’ll be well-versed with face recognition and detection and be able to apply your skills in the real world. All the codes and supporting files for this course will be available at https://github.com/PacktPublishing/Computer-Vision-Face-Recognition-Quick-Starter-in-Python

Who's this course for?

This course is designed for beginners or anyone who wants to get started with Python-based face recognition.

What you'll learn

  • Become well-versed with face detection and face recognition technology.
  • Understand how to install the Anaconda package Install dependencies and libraries such as dlib, OpenCV, and Pillow.
  • Learn how to perform face detection and face recognition.
  • Use the face distance parameter to calculate the magnitude of faces.
  • Create custom face make-up for an image with face landmark points.

Key Features

  • Use Python to detect and recognize faces from images and real-time webcam video.
  • Become well-versed with emotion detection.
  • Get up to speed with predicting age and gender from images and real-time webcam video.

Course Curriculum

About the Author

Abhilash Nelson

Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than 8 years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.. Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than eight years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.

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